Skip to main content

Repo-scoped Shellbrain CLI with explicit evidence-backed writes.

Project description

ShellBrain logo

ShellBrain

Long-term Memory for AI Agents.

Agents forget across sessions. They rediscover the same problems, repeat the same mistakes, and relearn what you already taught them. ShellBrain makes their work compound.

Recall in one command.

Episodic, empirical, conceptual. Three categories, one retrieval surface.


Architecture

Episodic knowledge is the evidence layer.

  • What actually happened in the session: your prompts, the agent's steps, tool calls, and outputs.

Empirical knowledge is the concrete extracted layer.

  • An ontology of problems, solutions, failed tactics, facts, preferences, changes.
  • This is case-based reasoning in a semantic graph.

Conceptual konwledge is the abstractive layer.

  • A higher-level concept graph with claims, relations, and implementations that link back to the concrete layer.
  • Progressive disclosure. agents get oriented first, then ask for depth only where tasks require it.

The episodic layer is truth. Empirical memory extracts. Concept memory abstracts. Each layer is grounded in the one beneath it.


How agents use ShellBrain

Working agents call recall. That is the normal interface they have to think about. One command, one carefully curated compact brief, with sources cited.

shellbrain recall --json '{"query":"what context matters for this migration lock timeout?","current_problem":{"goal":"fix the migration hang","surface":"db admin","obstacle":"lock timeout","hypothesis":"none yet"}}'

Lower-level commands exist for inner agents.

  • read, events, concept show, memory add, memory update, concept add, concept update

When a user explicitly says to store or teach Shellbrain something, working agents can call teach. It stores the statement as evidence and immediately runs Shellbrain's teach agent.

Working agents focus on only their work.


Principled and Disciplined

Memory that is grounded in evidence, small in scope, and asked for rather than pushed is memory that compounds. Everything else is noise for working agents.

A memory layer that cannot justify itself should not persist.


Install

curl -L shellbrain.ai/install | bash

Works for Codex, Claude Code, and Cursor. The installer runs shellbrain init for you. Repos register themselves on first use.

Requirements.

  • macOS or Linux, Python 3.11+, Docker for the managed local Postgres+pgvector runtime.

Upgrade for latest capabilities

shellbrain upgrade

The install script also works as an upgrade path: curl -L shellbrain.ai/upgrade | bash. Manual alternative: pipx upgrade shellbrain && shellbrain init.


How to Use ShellBrain

Use Shellbrain in your agent of choice. Then, just work normally.

Claude Code: Use /shellbrain to remember Shellbrain recall at the right task boundaries.

Codex: Use $shellbrain to remember Shellbrain recall at the right task boundaries.

Cursor: Use /shellbrain to remember Shellbrain recall at the right task boundaries.


Repair

shellbrain admin doctor to inspect. shellbrain init to repair if doctor flags it. Do not rerun init every session — it is not a no-op.


Docs

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

shellbrain-0.1.30.tar.gz (460.0 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

shellbrain-0.1.30-py3-none-any.whl (623.7 kB view details)

Uploaded Python 3

File details

Details for the file shellbrain-0.1.30.tar.gz.

File metadata

  • Download URL: shellbrain-0.1.30.tar.gz
  • Upload date:
  • Size: 460.0 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for shellbrain-0.1.30.tar.gz
Algorithm Hash digest
SHA256 ea7949ae5e9b42f81dcc89e2284ee744dd6bf8e9edc5d3ecbe2af214f87de9b7
MD5 692d8dbc710762bc91c98bf5b5a5b672
BLAKE2b-256 7882b94055c74d60407440f26bbbf26c95a8c88edf49f404d4ce3eba91de0bcb

See more details on using hashes here.

Provenance

The following attestation bundles were made for shellbrain-0.1.30.tar.gz:

Publisher: release.yml on cucupac/shellbrain

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

File details

Details for the file shellbrain-0.1.30-py3-none-any.whl.

File metadata

  • Download URL: shellbrain-0.1.30-py3-none-any.whl
  • Upload date:
  • Size: 623.7 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for shellbrain-0.1.30-py3-none-any.whl
Algorithm Hash digest
SHA256 eebaccfa166d3cd41a446cc1344944ab5c176f31b0cf3145e7e9d872258abcd7
MD5 4d10002f583ca5a5b1144885999ed56b
BLAKE2b-256 8136951638b91f4cb5aed54ccce82d5ff9739d286438f543b312d3b5e6654870

See more details on using hashes here.

Provenance

The following attestation bundles were made for shellbrain-0.1.30-py3-none-any.whl:

Publisher: release.yml on cucupac/shellbrain

Attestations: Values shown here reflect the state when the release was signed and may no longer be current.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page